Cardiovascular risk prediction in a New Zealand cohort of patients with known cardiovascular disease - a regional individual patient-level data linkage study

Abstract Background National health databases have been underutilised in the development of cardiovascular disease (CVD) risk prediction equations for people with known CVD, yet can inform population level practice and policy—including identification of health equity gaps, high-risk groups, and high-risk localities. With the recent introduction of novel and expensive preventive cardiovascular drugs, stratifying risk in patients with prior CVD could be required to inform cost-effective use of these medications in the future. Purpose We sought to develop 5-year CVD risk equations in adults with known history of CVD in Aotearoa New Zealand, using data from administrative health databases and characterize distribution of risk according to sex. Methods All people above 18 years of age with a history of CVD hospitalization, living in the Auckland and Northland regions of Aotearoa New Zealand (approximately one-third of the national population) on 1 January 2014 were included. Participants were followed for 5 years (31 December 2018) or until death or the outcome of interest, being any fatal or non-fatal CVD hospitalization (ischemic heart disease, heart failure, ischemic stroke, or peripheral artery disease) during follow-up. Sex-specific 5-year CVD risk prediction equations were developed using multivariable Fine and Gray models taking competing risk of non-cardiovascular death into account. Predictor variables included were age; ethnicity; deprivation level; time since most recent CVD hospitalization, history of smoking, heart failure, atrial fibrillation, chronic renal disease, and diabetes mellitus; use of anti-thrombotic, blood pressure-lowering, and lipid-lowering drugs; and blood levels of glycosylated hemoglobin (HbA1c), non-HDL cholesterol, and creatinine. Results The cohort comprised 42,130 men (median age: 68 years [interquartile range (IQR): 59–76]) and 31,717 women (median age: 70 years [IQR: 60–78]) with 12,875 and 8,734 observed events during follow-up, respectively. Sex-specific 5-year CVD risk prediction equations with excellent calibration (accuracy) were developed (Figure 1). Increasing age; high deprivation level; more recent CVD hospitalization; history of smoking, heart failure, atrial fibrillation, chronic renal disease, diabetes mellitus; use of blood-pressure lowering drugs; and high blood levels of HbA1c, non-HDL cholesterol, or creatinine were predictors of elevated risk. There was a wide range of predicted 5-year risk, with 15% of men and 24% of women having a predicted risk below 15%, and 24% and 20%, respectively, having a predicted risk of 40% or above (Figure 2). Conclusion This study demonstrates that it is possible to develop accurate CVD risk prediction equations from administrative health databases for patients with known CVD. Marked heterogeneity in 5-year risk of a subsequent CVD event emphasise that the current ‘one size fits all’ approach to secondary prevention of CVD requires review.Figure 1Figure 2